The invention provides an unmanned aerial vehicle task cooperative allocation method based on Q learning. The method comprises the steps: initializing parameters; obtaining a neighbor unmanned aerialvehicle set of each unmanned aerial vehicle according to the position information of the unmanned aerial vehicles and the tasks; determining a sensitive unmanned aerial vehicle and an indirect unmanned aerial vehicle; then, through each sensitive unmanned aerial vehicle, executing a task and sending a communication packet to a neighbor unmanned aerial vehicle; obtaining a Q table of each indirectunmanned aerial vehicle according to the communication packet; initializing a Q learning parameter; performing Q learning by the indirect unmanned aerial vehicle; and finally, obtaining an unmanned aerial vehicle task collaborative allocation result. According to the method, global information and local information are fully considered in the Q learning process of the unmanned aerial vehicle, optimization of the Q table of the unmanned aerial vehicle is achieved, and the convergence rate of task allocation is effectively increased on the basis that it is guaranteed that all tasks obtain the required execution amount.

Unmanned aerial vehicle task collaborative allocation method based on Q learning

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Unmanned aerial vehicle task collaborative allocation method based on Q learning